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New Trends in Ambient Intelligence Applications

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A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (12 October 2018) | Viewed by 34110

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Special Issue Editor

Prof. Dr. Juan Francisco De Paz Santana

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Guest Editor

Expert Systems and Applications Lab, Faculty of Science, University of Salamanca, 37008 Salamanca, Spain
Interests: ambient intelligence; artificial intelligence; multi-agent systems; wireless sensor networks; big data; edge computing; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The techniques and hardware involved in the development of Ambient Intelligence Systems are under a state of continuous evolution. This allows to develop hardware adapted systems and to deal with situations that were not approachable in different case studies. The use of new protocols, wireless sensor networks and devices has allowed to incorporate new sources of information; these can be processed thanks to the improvements in computing capacities and the reduced costs of the different devices. As a result, there is an increase in the use cases to which new trends in wireless sensor networks and devices can be applied. This Special Issue will focus on the use of new trends in WSN and devices that incorporate Artificial Intelligence techniques or Distributed Artificial Intelligence (multi-agent systems, virtual organizations, classifiers, neural networks, Bayesian networks, etc.) for information processing.

Topics of interest include, but are not limited to:

Mobile sensing applications
The application of machine learning to mobile sensing
Multiagent Systems
Ambient Assisted Living
Pervasive Computing
Context Aware Computing
Agent and Multiagent Systems for AmI
Mobile Computing
Computational Creativity
Sentient Computing
Context Modelling
Memory Assistant
System architecture for mobile sensing
Information fusion in light devices

Dr. Juan F. De Paz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Artificial Intelligence
wireless sensor networks
Information fusion

Published Papers (7 papers)

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Research

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25 pages, 7038 KiB

Open AccessArticle

Architecture to Embed Software Agents in Resource Constrained Internet of Things Devices

by Daniel H. De La Iglesia, Gabriel Villarrubia González, André Sales Mendes, Diego M. Jiménez-Bravo and Alberto L. Barriuso

Sensors 2019, 19(1), 100; https://doi.org/10.3390/s19010100 - 29 Dec 2018

Cited by 11 | Viewed by 3575

Abstract

Sensing systems in combination with treatment tools and intelligent information management are the basis on which the cities and urban environments of the future will be built. Progress in the research and development of these new and intelligent scenarios is essential to achieve the objectives of efficiency, integration, sustainability, and quality of life for people who live in cities. To achieve these objectives, it is essential to investigate the development of cheaper, more accurate, and smarter hardware devices, which will form the basis of the intelligent environments of the future. This article focuses on an approach based on intelligent multi-agent systems that are integrated into basic hardware devices for the Internet of Things (IoT). A multi-agent architecture is proposed for the fast, efficient, and intelligent management of the generated data. A layer of services adapted to the needs of the new intelligent environments is built on this architecture. With the aim of validating this architecture, a case study based on electric vehicles of the e-bike type is proposed. Full article

(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)

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15 pages, 3320 KiB

Open AccessArticle

Artificial Intelligence-Based Grading Quality of Bovine Blastocyst Digital Images: Direct Capture with Juxtaposed Lenses of Smartphone Camera and Stereomicroscope Ocular Lens

by Marcelo Fábio Gouveia Nogueira, Vitória Bertogna Guilherme, Micheli Pronunciate, Priscila Helena Dos Santos, Diogo Lima Bezerra da Silva and José Celso Rocha

Sensors 2018, 18(12), 4440; https://doi.org/10.3390/s18124440 - 15 Dec 2018

Cited by 7 | Viewed by 3826

Abstract

In this study, we developed an online graphical and intuitive interface connected to a server aiming to facilitate professional access worldwide to those facing problems with bovine blastocysts classification. The interface Blasto3Q, where 3Q refers to the three qualities of the blastocyst grading, contains a description of 24 variables that were extracted from the image of the blastocyst and analyzed by three Artificial Neural Networks (ANNs) that classify the same loaded image. The same embryo (i.e., the biological specimen) was submitted to digital image capture by the control group (inverted microscope with 40× magnification) and the experimental group (stereomicroscope with maximum of magnification plus 4× zoom from the cell phone camera). The images obtained from the control and experimental groups were uploaded on Blasto3Q. Each image from both sources was evaluated for segmentation and submitted (only if it could be properly or partially segmented) for automatic quality grade classification by the three ANNs of the Blasto3Q program. Adjustments on the software program through the use of scaling algorithm software were performed to ensure the proper search and segmentation of the embryo in the raw images when they were captured by the smartphone, since this source produced small embryo images compared with those from the inverted microscope. With this new program, 77.8% of the images from smartphones were successfully segmented and from those, 85.7% were evaluated by the Blasto3Q in agreement with the control group. Full article

(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)

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14 pages, 1581 KiB

Open AccessArticle

SDN Based End-to-End Inter-Domain Routing Mechanism for Mobility Management and Its Evaluation

by Misumi Hata, Mustafa Soylu, Satoru Izumi, Toru Abe and Takuo Suganuma

Sensors 2018, 18(12), 4228; https://doi.org/10.3390/s18124228 - 02 Dec 2018

Cited by 6 | Viewed by 3415

Abstract

Nowadays, due to the widespread usage of mobile devices and wireless network technologies, we can use various ICT services almost anytime, anywhere even if we are changing our location at that moment. Therefore, mobility management technology have been attracting attention. This technology is to keep communication alive even when a mobile node (MN), which is communicating with the server or some nodes, moves to another network domain. Software Defined Networking (SDN) is used for mobility management to realize effective intra-domain routing that optimizes routes when an MN moves inside an SDN domain. However, many of the approaches mainly focus on intra-domain routing and it is difficult to optimize inter-domain route. In this paper, we focus on this routing optimization problem and propose an SDN based end-to-end routing mechanism specified for mobility management. The proposed routing mechanism can optimize an end-to-end route based on various parameters such as bandwidth, number of domains, and flow operations for mobility after an MN has moved across SDN domains. We carried out some simulational experimentations to evaluate the effect of proposal. It is shown that the proposed routing mechanism can reduce communication delay and enhance network performance. Thus, the proposed routing mechanism can realize effective ICT services. Full article

(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)

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30 pages, 6560 KiB

Open AccessArticle

Ambient Intelligence Environment for Home Cognitive Telerehabilitation

by Miguel Oliver, Miguel A. Teruel, José Pascual Molina, Dulce Romero-Ayuso and Pascual González

Sensors 2018, 18(11), 3671; https://doi.org/10.3390/s18113671 - 29 Oct 2018

Cited by 23 | Viewed by 5605

Abstract

Higher life expectancy is increasing the number of age-related cognitive impairment cases. It is also relevant, as some authors claim, that physical exercise may be considered as an adjunctive therapy to improve cognition and memory after strokes. Thus, the integration of physical and cognitive therapies could offer potential benefits. In addition, in general these therapies are usually considered boring, so it is important to include some features that improve the motivation of patients. As a result, computer-assisted cognitive rehabilitation systems and serious games for health are more and more present. In order to achieve a continuous, efficient and sustainable rehabilitation of patients, they will have to be carried out as part of the rehabilitation in their own home. However, current home systems lack the therapist’s presence, and this leads to two major challenges for such systems. First, they need sensors and actuators that compensate for the absence of the therapist’s eyes and hands. Second, the system needs to capture and apply the therapist’s expertise. With this aim, and based on our previous proposals, we propose an ambient intelligence environment for cognitive rehabilitation at home, combining physical and cognitive activities, by implementing a Fuzzy Inference System (FIS) that gathers, as far as possible, the knowledge of a rehabilitation expert. Moreover, smart sensors and actuators will attempt to make up for the absence of the therapist. Furthermore, the proposed system will feature a remote monitoring tool, so that the therapist can supervise the patients’ exercises. Finally, an evaluation will be presented where experts in the rehabilitation field showed their satisfaction with the proposed system. Full article

(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)

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22 pages, 1819 KiB

Open AccessArticle

Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator

by Khaoula Ghefiri, Soufiene Bouallègue, Izaskun Garrido, Aitor J. Garrido and Joseph Haggège

Sensors 2018, 18(5), 1317; https://doi.org/10.3390/s18051317 - 24 Apr 2018

Cited by 11 | Viewed by 4901

Abstract

Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG) systems aim to provide clean and reliable electrical power. However, the power captured from tidal currents is highly disturbed due to the swell effect and the periodicity of the tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN) is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT) generated from the ANN block. In case of strong tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances. Full article

(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)

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18 pages, 9337 KiB

Open AccessArticle

Active and Assisted Living Ecosystem for the Elderly

by Isabel Marcelino, Rosalía Laza, Patrício Domingues, Silvana Gómez-Meire, Florentino Fdez-Riverola and António Pereira

Sensors 2018, 18(4), 1246; https://doi.org/10.3390/s18041246 - 17 Apr 2018

Cited by 22 | Viewed by 5861

Abstract

A novel ecosystem to promote the physical, emotional and psychic health and well-being of the elderly is presented. Our proposal was designed to add several services developed to meet the needs of the senior population, namely services to improve social inclusion and increase contribution to society. Moreover, the solution monitors the vital signs of elderly individuals, as well as environmental parameters and behavior patterns, in order to seek eminent danger situations and predict potential hazardous issues, acting in accordance with the various alert levels specified for each individual. The platform was tested by seniors in a real scenario. The experimental results demonstrated that the proposed ecosystem was well accepted and is easy to use by seniors. Full article

(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)

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Review

Jump to: Research

23 pages, 449 KiB

Open AccessReview

Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review

by Ivan Miguel Pires, Rui Santos, Nuno Pombo, Nuno M. Garcia, Francisco Flórez-Revuelta, Susanna Spinsante, Rossitza Goleva and Eftim Zdravevski

Sensors 2018, 18(1), 160; https://doi.org/10.3390/s18010160 - 09 Jan 2018

Cited by 27 | Viewed by 5817

Abstract

An increase in the accuracy of identification of Activities of Daily Living (ADL) is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL) tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices. A comprehensive literature search was conducted in order to identify relevant English language works aimed at the identification of the environment of ADLs using data acquired with mobile devices, published between 2002 and 2017. In total, 40 studies were analyzed and selected from 115 citations. The results highlight several audio fingerprinting techniques, including Modified discrete cosine transform (MDCT), Mel-frequency cepstrum coefficients (MFCC), Principal Component Analysis (PCA), Fast Fourier Transform (FFT), Gaussian mixture models (GMM), likelihood estimation, logarithmic moduled complex lapped transform (LMCLT), support vector machine (SVM), constant Q transform (CQT), symmetric pairwise boosting (SPB), Philips robust hash (PRH), linear discriminant analysis (LDA) and discrete cosine transform (DCT). Full article

(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)

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